Safe and secure platooning of Automated Guided Vehicles in Industry 4.0
2021 (English)In: Journal of systems architecture, ISSN 1383-7621, E-ISSN 1873-6165, Vol. 121, article id 102309Article in journal (Refereed) Published
Abstract [en]
Automated Guided Vehicles (AGVs) are widely used for materials transportation. Operating them in a platooned manner has the potential to improve safety, security and efficiency, control overall traffic flow and reduce resource usage. However, the published studies on platooning focus mainly on the design of technical solutions in the context of automotive domain. In this paper we focus on a largely unexplored theme of platooning in production sites transformed to the Industry 4.0, with the aim of providing safety and security assurances. We present an overall approach for a fault- and threat tolerant platooning for materials transportation in production environments. Our functional use cases include the platoon control for collision avoidance, data acquisition and processing by considering range, and connectivity with fog and cloud levels. To perform the safety and security analyses, the Hazard and Operability (HAZOP) and Threat and Operability (THROP) techniques are used. Based on the results obtained from them, the safety and security requirements are derived for the identification and prevention/mitigation of potential platooning hazards, threats and vulnerabilities. The assurance cases are constructed to show the acceptable safety and security of materials transportation using AGV platooning. We leveraged a simulation-based digital twin for performing the verification and validation as well as finetuning of the platooning strategy. Simulation data is gathered from digital twin to monitor platoon operations, identify unexpected or incorrect behaviour, evaluate the potential implications, trigger control actions to resolve them, and continuously update assurance cases. The applicability of the AGV platooning is demonstrated in the context of a quarry site. © 2021 The Authors
Place, publisher, year, edition, pages
Elsevier B.V. , 2021. Vol. 121, article id 102309
Keywords [en]
AGVs, Assurance cases, Dynamic risk management, Industry 4.0, Platooning, Safety, Security, Accident prevention, Automatic guided vehicles, Data acquisition, Data handling, Hazards, Materials handling, Mobile robots, Assurance case, Automated guided vehicles, Dynamic risks, Material transportation, Risks management, Safety and securities, Safety controls, Risk management
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:ri:diva-56908DOI: 10.1016/j.sysarc.2021.102309Scopus ID: 2-s2.0-85118482447OAI: oai:DiVA.org:ri-56908DiVA, id: diva2:1613491
Note
Funding details: Horizon 2020 Framework Programme, H2020; Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding details: VINNOVA; Funding details: Horizon 2020; Funding details: Electronic Components and Systems for European Leadership, ECSEL, 876038 4 4; Funding text 1: This work is supported by InSecTT (Intelligent Secure Trustable Things), ESCAPE (Efficient and effective functional safety for complex autonomous production systems) and FiC (Future factories in the Cloud) projects. InSecTT has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 876038 4 4 . The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Sweden, Spain, Italy, France, Portugal, Ireland, Finland, Slovenia, Poland, Netherlands, Turkey. ESCAPE project has received funding from the PiiA (Process industrial IT and Automation) program which is financed through Vinnova , while the FiC project is funded by the SSF (Swedish Foundation for Strategic Research) . The first author has also participated during the tenure of an ERCIM “Alain Bensoussan” Fellowship Programme.; Funding text 2: This work is supported by InSecTT (Intelligent Secure Trustable Things), ESCAPE (Efficient and effective functional safety for complex autonomous production systems) and FiC (Future factories in the Cloud) projects. InSecTT has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 8760384. The JU receives support from the European Union's Horizon 2020 research and innovation programme and Austria, Sweden, Spain, Italy, France, Portugal, Ireland, Finland, Slovenia, Poland, Netherlands, Turkey. ESCAPE project has received funding from the PiiA (Process industrial IT and Automation) program which is financed through Vinnova, while the FiC project is funded by the SSF (Swedish Foundation for Strategic Research). The first author has also participated during the tenure of an ERCIM ?Alain Bensoussan? Fellowship Programme.
2021-11-222021-11-222021-11-22Bibliographically approved